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Schäfer S, Smelik M, Sysoev O, Zhao Y, Eklund D, Lilja S, Gustafsson M, Heyn H, Julia A, Kovács IA, Loscalzo J, Marsal S, Zhang H, Li X, Gawel D, Wang H, Benson M. scDrugPrio: a framework for the analysis of single-cell transcriptomics to address multiple problems in precision medicine in immune-mediated inflammatory diseases. Genome Med 2024; 16:42. [PMID: 38509600 PMCID: PMC10956347 DOI: 10.1186/s13073-024-01314-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 03/12/2024] [Indexed: 03/22/2024] Open
Abstract
BACKGROUND Ineffective drug treatment is a major problem for many patients with immune-mediated inflammatory diseases (IMIDs). Important reasons are the lack of systematic solutions for drug prioritisation and repurposing based on characterisation of the complex and heterogeneous cellular and molecular changes in IMIDs. METHODS Here, we propose a computational framework, scDrugPrio, which constructs network models of inflammatory disease based on single-cell RNA sequencing (scRNA-seq) data. scDrugPrio constructs detailed network models of inflammatory diseases that integrate information on cell type-specific expression changes, altered cellular crosstalk and pharmacological properties for the selection and ranking of thousands of drugs. RESULTS scDrugPrio was developed using a mouse model of antigen-induced arthritis and validated by improved precision/recall for approved drugs, as well as extensive in vitro, in vivo, and in silico studies of drugs that were predicted, but not approved, for the studied diseases. Next, scDrugPrio was applied to multiple sclerosis, Crohn's disease, and psoriatic arthritis, further supporting scDrugPrio through prioritisation of relevant and approved drugs. However, in contrast to the mouse model of arthritis, great interindividual cellular and gene expression differences were found in patients with the same diagnosis. Such differences could explain why some patients did or did not respond to treatment. This explanation was supported by the application of scDrugPrio to scRNA-seq data from eleven individual Crohn's disease patients. The analysis showed great variations in drug predictions between patients, for example, assigning a high rank to anti-TNF treatment in a responder and a low rank in a nonresponder to that treatment. CONCLUSIONS We propose a computational framework, scDrugPrio, for drug prioritisation based on scRNA-seq of IMID disease. Application to individual patients indicates scDrugPrio's potential for personalised network-based drug screening on cellulome-, genome-, and drugome-wide scales. For this purpose, we made scDrugPrio into an easy-to-use R package ( https://github.com/SDTC-CPMed/scDrugPrio ).
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Affiliation(s)
- Samuel Schäfer
- Centre for Personalised Medicine, Linköping University, Linköping, Sweden
- Department of Gastroenterology and Hepatology, University Hospital, Linköping, Sweden
| | - Martin Smelik
- Postal Address: LIME/Medical Digital Twin Research Group, Division of ENT, CLINTEC, Karolinska Institute, Tomtebodavägen 18A. 171 65 Solna, Stockholm, Sweden
| | - Oleg Sysoev
- Division of Statistics and Machine Learning, Department of Computer and Information Science, Linkoping University, Linköping, Sweden
| | - Yelin Zhao
- Postal Address: LIME/Medical Digital Twin Research Group, Division of ENT, CLINTEC, Karolinska Institute, Tomtebodavägen 18A. 171 65 Solna, Stockholm, Sweden
| | - Desiré Eklund
- Centre for Personalised Medicine, Linköping University, Linköping, Sweden
| | - Sandra Lilja
- Centre for Personalised Medicine, Linköping University, Linköping, Sweden
- Mavatar, Inc, Stockholm, Sweden
| | - Mika Gustafsson
- Division for Bioinformatics, Department of Physics, Chemistry and Biology, Linköping University, Linköping, Sweden
| | - Holger Heyn
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08028, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), 08002, Barcelona, Spain
| | - Antonio Julia
- Grup de Recerca de Reumatologia, Institut de Recerca Vall d'Hebron, Barcelona, Spain
| | - István A Kovács
- Department of Physics and Astronomy, Northwestern University, Evanston, IL, 60208, USA
- Northwestern Institute On Complex Systems, Northwestern University, Evanston, IL, 60208, USA
| | - Joseph Loscalzo
- Division of Cardiovascular Medicine, Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Sara Marsal
- Grup de Recerca de Reumatologia, Institut de Recerca Vall d'Hebron, Barcelona, Spain
| | - Huan Zhang
- Centre for Personalised Medicine, Linköping University, Linköping, Sweden
| | - Xinxiu Li
- Postal Address: LIME/Medical Digital Twin Research Group, Division of ENT, CLINTEC, Karolinska Institute, Tomtebodavägen 18A. 171 65 Solna, Stockholm, Sweden
| | | | - Hui Wang
- Postal Address: LIME/Medical Digital Twin Research Group, Division of ENT, CLINTEC, Karolinska Institute, Tomtebodavägen 18A. 171 65 Solna, Stockholm, Sweden
- Jiangsu Key Laboratory of Immunity and Metabolism, Department of Pathogenic Biology and Immunology, Xuzhou Medical University, Jiangsu, China
| | - Mikael Benson
- Postal Address: LIME/Medical Digital Twin Research Group, Division of ENT, CLINTEC, Karolinska Institute, Tomtebodavägen 18A. 171 65 Solna, Stockholm, Sweden.
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Schäfer S, Smelik M, Sysoev O, Zhao Y, Eklund D, Lilja S, Gustafsson M, Heyn H, Julia A, Kovács IA, Loscalzo J, Marsal S, Zhang H, Li X, Gawel D, Wang H, Benson M. scDrugPrio: A framework for the analysis of single-cell transcriptomics to address multiple problems in precision medicine in immune-mediated inflammatory diseases. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.08.566249. [PMID: 38014022 PMCID: PMC10680570 DOI: 10.1101/2023.11.08.566249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Background Ineffective drug treatment is a major problem for many patients with immune-mediated inflammatory diseases (IMIDs). Important reasons are the lack of systematic solutions for drug prioritisation and repurposing based on characterisation of the complex and heterogeneous cellular and molecular changes in IMIDs. Methods Here, we propose a computational framework, scDrugPrio, which constructs network models of inflammatory disease based on single-cell RNA sequencing (scRNA-seq) data. scDrugPrio constructs detailed network models of inflammatory diseases that integrate information on cell type-specific expression changes, altered cellular crosstalk and pharmacological properties for the selection and ranking of thousands of drugs. Results scDrugPrio was developed using a mouse model of antigen-induced arthritis and validated by improved precision/recall for approved drugs, as well as extensive in vitro, in vivo, and in silico studies of drugs that were predicted, but not approved, for the studied diseases. Next, scDrugPrio was applied to multiple sclerosis, Crohn's disease, and psoriatic arthritis, further supporting scDrugPrio through prioritisation of relevant and approved drugs. However, in contrast to the mouse model of arthritis, great interindividual cellular and gene expression differences were found in patients with the same diagnosis. Such differences could explain why some patients did or did not respond to treatment. This explanation was supported by the application of scDrugPrio to scRNA-seq data from eleven individual Crohn's disease patients. The analysis showed great variations in drug predictions between patients, for example, assigning a high rank to anti-TNF treatment in a responder and a low rank in a nonresponder to that treatment. Conclusion We propose a computational framework, scDrugPrio, for drug prioritisation based on scRNA-seq of IMID disease. Application to individual patients indicates scDrugPrio's potential for personalised network-based drug screening on cellulome-, genome-, and drugome-wide scales. For this purpose, we made scDrugPrio into an easy-to-use R package (https://github.com/SDTC-CPMed/scDrugPrio).
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Affiliation(s)
- Samuel Schäfer
- Centre for Personalised Medicine, Linköping University; Linköping, Sweden
- Department of Gastroenterology and Hepatology, University Hospital, Linköping, Sweden
| | - Martin Smelik
- Centre for Personalised Medicine, Linköping University; Linköping, Sweden
- Division of ENT, CLINTEC, Karolinska Institute, Stockholm, Sweden
| | - Oleg Sysoev
- Division of Statistics and Machine Learning, Department of Computer and Information Science, Linkoping University; Linköping, Sweden
| | - Yelin Zhao
- Centre for Personalised Medicine, Linköping University; Linköping, Sweden
- Division of ENT, CLINTEC, Karolinska Institute, Stockholm, Sweden
| | - Desiré Eklund
- Centre for Personalised Medicine, Linköping University; Linköping, Sweden
| | - Sandra Lilja
- Centre for Personalised Medicine, Linköping University; Linköping, Sweden
- Mavatar, Inc., Stockholm. Sweden
| | - Mika Gustafsson
- Division for Bioinformatics, Department of Physics, Chemistry and Biology, Linköping University; Linköping, Sweden
| | - Holger Heyn
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08028 Barcelona, Spain
- Universitat Pompeu Fabra (UPF), 08002 Barcelona, Spain
| | - Antonio Julia
- Grup de Recerca de Reumatologia, Institut de Recerca Vall d’Hebron, Barcelona, España
| | - István A. Kovács
- Department of Physics and Astronomy, Northwestern University, Evanston, IL 60208, USA
- Northwestern Institute on Complex Systems, Northwestern University, Evanston, IL 60208, USA
| | - Joseph Loscalzo
- Division of Cardiovascular Medicine, Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School; Boston, MA, USA
| | - Sara Marsal
- Grup de Recerca de Reumatologia, Institut de Recerca Vall d’Hebron, Barcelona, España
| | - Huan Zhang
- Centre for Personalised Medicine, Linköping University; Linköping, Sweden
| | - Xinxiu Li
- Centre for Personalised Medicine, Linköping University; Linköping, Sweden
- Division of ENT, CLINTEC, Karolinska Institute, Stockholm, Sweden
| | - Danuta Gawel
- Centre for Personalised Medicine, Linköping University; Linköping, Sweden
- Mavatar, Inc., Stockholm. Sweden
| | - Hui Wang
- Northwestern Institute on Complex Systems, Northwestern University, Evanston, IL 60208, USA
| | - Mikael Benson
- Centre for Personalised Medicine, Linköping University; Linköping, Sweden
- Division of ENT, CLINTEC, Karolinska Institute, Stockholm, Sweden
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Xie H, Chen L, Zhang H, Wang J, Zang Y, Zhan M, Gu F, Wang S, He S. Increased expressions of CD123, CD63, CD203c, and Fc epsilon receptor I on blood leukocytes of allergic asthma. Front Mol Biosci 2022; 9:907092. [PMID: 36032674 PMCID: PMC9403487 DOI: 10.3389/fmolb.2022.907092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 06/27/2022] [Indexed: 11/28/2022] Open
Abstract
Background: Altered basophil identification markers have been discovered to associate with allergic asthma (AA) in recent years. However, little is known about the expression of basophil markers in blood granulocytes. Aim: To parallel test blood basophils in peripheral blood mononuclear cell (PBMC) and granulocyte populations of patients with AA and AA combined with allergic rhinitis (ARA) Methods: The expressions of surface molecules were determined via flow cytometry. CD123 expressing cells in blood were isolated using a cell sorting technique, and mouse AA models were employed for in vivo study. Results: The numbers of CD123+HLA-DR− cells in the granulocytes of AA and ARA patients markedly increased. However, only 49.7% of CD123+HLA-DR− cells in granulocytes and 99.0% of CD123+HLA-DR− cells in PBMCs were basophils. Almost all CD123+HLA-DR− cells expressed CD63 regardless in granulocytes or PBMC. The numbers of CD63, Fc epsilon receptor I (FcεRI), and CD203c expressing cells markedly enhanced in CD123+HLA-DR− granulocytes of AA and ARA patients. Mean fluorescence intensity (MFI) of CD63 and CD203c expressions on CD123+HLA-DR− PBMC and granulocytes of AA and ARA patients dramatically elevated. House dust mite extract (HDME) and Artemisia sieversiana wild allergen extract (ASWE) enhanced the numbers of CD63+CD123+HLA-DR− granulocytes and PBMC and the MFI of CD203c expression on CD123+HLA-DR− granulocyte of AA and ARA patients. Histamine, tryptase, and PGD2 enhanced proportions of CD123+ KU812 cells. ASWE- and HDME-induced AA mice showed upregulated CD63 expression on basophils. In conclusion, upregulated expressions of CD123, CD203c, CD63, and FcεRIα in PBMC and granulocytes of patients with AA and ARA suggest that CD123+HLA-DR− cells may contribute to the development of AA and ARA.
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Affiliation(s)
- Hua Xie
- The PLA Center of Respiratory and Allergic Disease Diagnosing Management, General Hospital of Northern Theater Command, Shenyang, China
- Allergy and Clinical Immunology Research Centre, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, China
| | - Liping Chen
- Translational Medicine Institute, Shenyang Medical College, Shenyang, China
- Department of Respiratory and Critical Care Medicine, The Second Hospital of Senyang Medical College, Shenyang, China
| | - Huiyun Zhang
- Translational Medicine Institute, Shenyang Medical College, Shenyang, China
| | - Junling Wang
- Allergy and Clinical Immunology Research Centre, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, China
| | - Yanyan Zang
- Allergy and Clinical Immunology Research Centre, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, China
| | - Mengmeng Zhan
- Translational Medicine Institute, Shenyang Medical College, Shenyang, China
| | - Fangqiu Gu
- Allergy and Clinical Immunology Research Centre, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, China
| | - Shunlan Wang
- Central Laboratory, Affiliated Haikou Hospital of Xiangya Medical College, Central South University, Haikou, China
| | - Shaoheng He
- The PLA Center of Respiratory and Allergic Disease Diagnosing Management, General Hospital of Northern Theater Command, Shenyang, China
- Allergy and Clinical Immunology Research Centre, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, China
- *Correspondence: Shaoheng He,
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